class_docstr: Reference: https://docs.aleph-alpha.com/api/complete/
  
  The `AlephAlphaConfig` class represents the configuration for the Aleph Alpha API. Here are the properties:
  
  - `maximum_tokens` (integer, required): The maximum number of tokens to be generated by the completion. The sum of input tokens and maximum tokens may not exceed 2048.
  
  - `minimum_tokens` (integer, optional; default value: 0): Generate at least this number of tokens before an end-of-text token is generated.
  
  - `echo` (boolean, optional; default value: false): Whether to echo the prompt in the completion.
  
  - `temperature` (number, nullable; default value: 0): Adjusts how creatively the model generates outputs. Use combinations of temperature, top_k, and top_p sensibly.
  
  - `top_k` (integer, nullable; default value: 0): Introduces randomness into token generation by considering the top k most likely options.
  
  - `top_p` (number, nullable; default value: 0): Adds randomness by considering the smallest set of tokens whose cumulative probability exceeds top_p.
  
  - `presence_penalty`, `frequency_penalty`, `sequence_penalty` (number, nullable; default value: 0): Various penalties that can reduce repetition.
  
  - `sequence_penalty_min_length` (integer; default value: 2): Minimum number of tokens to be considered as a sequence.
  
  - `repetition_penalties_include_prompt`, `repetition_penalties_include_completion`, `use_multiplicative_presence_penalty`,`use_multiplicative_frequency_penalty`,`use_multiplicative_sequence_penalty` (boolean, nullable; default value: false): Various settings that adjust how the repetition penalties are applied.
  
  - `penalty_bias` (string, nullable): Text used in addition to the penalized tokens for repetition penalties.
  
  - `penalty_exceptions` (string[], nullable): Strings that may be generated without penalty.
  
  - `penalty_exceptions_include_stop_sequences` (boolean, nullable; default value: true): Include all stop_sequences in penalty_exceptions.
  
  - `best_of` (integer, nullable; default value: 1): The number of completions will be generated on the server side.
  
  - `n` (integer, nullable; default value: 1): The number of completions to return.
  
  - `logit_bias` (object, nullable): Adjust the logit scores before sampling.
  
  - `log_probs` (integer, nullable): Number of top log probabilities for each token generated.
  
  - `stop_sequences` (string[], nullable): List of strings that will stop generation if they're generated.
  
  - `tokens` (boolean, nullable; default value: false): Flag indicating whether individual tokens of the completion should be returned or not.
  
  - `raw_completion` (boolean; default value: false): if True, the raw completion of the model will be returned.
  
  - `disable_optimizations` (boolean, nullable; default value: false): Disables any applied optimizations to both your prompt and completion.
  
  - `completion_bias_inclusion`, `completion_bias_exclusion` (string[], default value: []): Set of strings to bias the generation of tokens.
  
  - `completion_bias_inclusion_first_token_only`, `completion_bias_exclusion_first_token_only` (boolean; default value: false): Consider only the first token for the completion_bias_inclusion/exclusion.
  
  - `contextual_control_threshold` (number, nullable): Control over how similar tokens are controlled.
  
  - `control_log_additive` (boolean; default value: true): Method of applying control to attention scores.
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code: def get_config(cls):
      return {
          k: v
          for k, v in cls.__dict__.items()
          if not k.startswith("__")
          and not isinstance(
              v,
              (
                  types.FunctionType,
                  types.BuiltinFunctionType,
                  classmethod,
                  staticmethod,
              ),
          )
          and v is not None
      }
  
file_path: litellm/litellm/llms/aleph_alpha.py
imports: import os, types
  import json
  from enum import Enum
  import requests
  import time
  from typing import Callable, Optional
  import litellm
  from litellm.utils import ModelResponse, Choices, Message, Usage
  import httpx
label_desc: Use image node_id 2 for calling the AlephAlphaConfig obj's underlying member method code with example usage: obj.get_config(cls) and returns: unknown